{"id":"W2270834142","doi":"10.4271/2000-01-0318","title":"Adding Value Through Predictive Analysis","year":2000,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Engineering and Test Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nova Chemicals (Canada)","funders":"","keywords":"Value (mathematics); Computer science; Predictive value; Machine learning; Medicine; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004511786,0.0009375456,0.00129301,0.0003250352,0.0002991291,0.0001285948,0.000949166,0.0008982028,0.00132046],"category_scores_gemma":[0.0002318724,0.0008652962,0.000823687,0.002223554,0.0004202313,0.0005847169,0.0001237211,0.00142063,0.0003878616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004251772,"about_ca_system_score_gemma":0.00003579004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007164272,"about_ca_topic_score_gemma":0.008840327,"domain_scores_codex":[0.9956159,0.0001079818,0.001134355,0.001079927,0.0009027175,0.001159104],"domain_scores_gemma":[0.9974159,0.0004686561,0.00009214773,0.001565897,0.00006499789,0.0003923824],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001439591,0.0002572556,0.0002943927,0.0001489261,0.001096186,0.0001058052,0.0001463505,0.06725855,0.9066457,0.01324615,0.006194853,0.00446187],"study_design_scores_gemma":[0.0005354522,0.0005920705,0.8705524,0.0002803662,0.0006157028,0.00007906116,0.0000675602,0.0000185219,0.0001332224,0.0006972235,0.1253355,0.001092919],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3896188,0.00181975,0.00004956311,0.0008908208,0.0007000909,0.001400595,0.0003010365,0.02135337,0.583866],"genre_scores_gemma":[0.9933908,0.0006940574,0.00362836,0.0004079545,0.0003085228,0.0003663996,0.00008924801,0.000215394,0.0008992889],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9065125,"threshold_uncertainty_score":0.9995925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007741912572369339,"score_gpt":0.2200810633859706,"score_spread":0.2123391508136013,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}